Advisory / consultancy
Diagnose, plan, and design governance.
Investor briefing
Speed is no longer the scarce asset. Controlled speed is.
Agentic Engineering Governance, powered by Software Dark Factory, helps engineering teams assess and govern AI-assisted delivery before scaling agentic work across the company.
We start with an assisted repo readiness assessment: an evidence-backed report showing blockers, risks, and next actions for governed agentic delivery.
The first wedge is assisted, evidence-led, and claim-bounded.
Painful shift
AI agents are increasing engineering output faster than existing review systems were designed to control.
Teams are already experimenting with AI-assisted coding, but leadership still needs evidence, reviewability, accountability, and confidence before scaling it.
- more code and changes to review
- shadow AI usage and unmanaged process drift
- unclear evidence behind agent-generated work
- CI and PR review remain necessary, but not enough on their own
Market pressure
The market is validating the problem. The missing layer is delivery governance.
Consultancies and AI governance platforms are helping companies diagnose, plan, and manage AI risk. Review, security, and monitoring tools help manage symptoms once work is already happening.
Software Dark Factory starts earlier: inside the engineering delivery workflow, with repo readiness, Assessment Packets, evidence, blocker classification, review paths, and implementation-ready next actions.
Regulation adds time pressure, but the operational pressure is already here: teams are using AI before governance workflows are ready.
Governance / security / review tools
Manage inventory, compliance, runtime risk, review load, drift, and security findings.
Delivery governance layer
Make agentic engineering work reviewable, evidenced, and repeatable before it scales.
The wedge
The wedge: assisted repo readiness assessment.
We assess whether a repo is ready for governed agentic delivery and return an evidence-backed readiness report with blockers, risks, boundaries, and next actions.
- evidence-backed readiness report
- blocker classification
- risk and boundary summary
- practical next actions
- optional assisted factoryization path
What exists now
The assisted V0 flow is packet-first.
The Assessment Packet is the interface between customer intent, evidence, and action. The Software Dark Factory model is the repeatable factory process around it: intent, evidence, review, boundaries, readiness report, implementation path, governed workflow, and governed front door.
Assessment request
A lightweight request starts the assisted workflow.
Assessment Packet
Customer intent becomes a reviewable handoff for operator and agent work.
Repo evidence collection
Available repo, workflow, and delivery evidence is gathered before claims are made.
Readiness interpretation
Findings map evidence to readiness states and risks.
Blocker classification
The report separates blockers, boundaries, and practical next actions.
Readiness report
The customer receives blockers, risks, boundaries, and next actions in an evidence-backed report.
Implementation path
The report becomes a practical path toward assisted factoryization and governed workflow.
Governed front door
The product path is a controlled entry point for agentic work with intent, evidence, checks, review, and approval.
Proof so far
Current progress is visible and evidence-led.
GTM site live
The public surface is deployed and aligned around governed agentic delivery.
Request capture working
Assessment interest can be captured without repo access or automation claims.
Packet export contract available
Stored requests can be serialized into packet-compatible YAML for operator handoff.
Bootstrap packet import available
The fulfilment engine can receive packet-shaped assessment context.
Evidence collection available
Local repo evidence collection exists for assisted assessment work.
Evidence-to-report mapping available
Assessment evidence can be mapped into report-ready findings.
Assisted report generation available
Operator-reviewed assessment reports can be produced from gathered evidence.
Reference packet complete
The first reference assessment packet is complete for proof and iteration.
Controlled receiver enforcement proven
Rails and TypeScript receiver proofs show the governance path can become enforceable in controlled settings.
Trust discipline
Packet-first and operator-assisted before hosted automation claims.
We are deliberately packet-first and operator-assisted before claiming hosted self-serve automation.
Current V0 does not yet claim self-serve repo scanning, hosted enforcement, automatic repo mutation, or production/customer governance.
Business machine
Assisted delivery becomes the productization path.
The first wedge is deliberately service-assisted because that is where the fastest learning and strongest evidence are created.
Each assessment sharpens the packet, report, playbooks, and repeatable implementation path.
founder-led authority
GTM site
assisted assessment request
Assessment Packet
readiness report
paid implementation / factoryization
recurring governance workflow
future hosted control plane
Wider model
Governance is the wedge. The factory model is the bigger company.
The same primitives that make AI-assisted software delivery safe also make other company workflows more repeatable: intent, playbooks, evidence, review, approval, and continuous improvement.
Software engineering is the starting point because the pain is immediate and measurable. Over time, the same operating model can extend into marketing, sales, operations, support, and other repeatable work.
Why this team
Founder-market fit: governance from the full SDLC.
The Software Dark Factory thesis comes from 20+ years of startup engineering where the same person often carries the work from ambiguous idea through build, test, deploy, production, maintenance, and scale.
Explore was the proof surface: a real Rails product designed around agent-accessible profiles and agent-first workflows.
Software Dark Factory is the governance product path extracted from that work.
Founder memo
Read the founder-market-fit memo behind the governance thesis.
Read the founder memoExplore proof surface
Explore was the original proof surface for the agent-first workflow and operating model.
Explore the original proof surfaceFollow the founder's work on agentic engineering and full-SDLC governance.
Connect on LinkedInWhy now / why us
The first wave was AI coding speed. The second wave is governed AI delivery.
The Software Dark Factory model has been built from real agentic development workflows, hands-on engineering leadership, public proof surfaces, and controlled receiver experiments.
Explore remains useful as the original proof ground for agent-first workflows. The commercial focus is now Agentic Engineering Governance.
Investor materials
A compact briefing set.
Investor deck
Download the current Agentic Engineering Governance investor deck.
Download investor deckSample assessment report
Illustrative V0 report showing readiness states, blockers, evidence, and next steps.
View sample assessmentAssessment journey
Demo-backed view of how a readiness assessment leads to a report, implementation path, governed workflow, and front door.
View assessment journeyOptional demo / Loom
Short walkthrough of the packet-first assessment workflow and commercial wedge.
Coming soonInvestor conversation
Help turn the assisted assessment wedge into a repeatable product.
We are looking for aligned investors, advisors, and design partners to help turn the assisted assessment workflow into a repeatable productized wedge.